BACKGROUND: Under-5 mortality remains a critical social indicator of a country's development and economic sustainability, particularly in developing nations like Bangladesh. This study employs machine learning models, including Linear Regression, Rid...
BACKGROUND: Machine learning and AI promise to revolutionize the way we leverage medical imaging data for improving care but require large datasets to train computational models that can be implemented in clinical practice. However, processing large ...
Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
Feb 6, 2025
BACKGROUND: In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple ...
BACKGROUND: Knee kinematics during daily activities reflect disease severity preoperatively and are associated with clinical outcomes after total knee arthroplasty (TKA). It is widely believed that measured kinematics would be useful for preoperative...
A key molecular dysfunction in heart failure is the reduced activity of the cardiac sarcoplasmic reticulum Ca-ATPase (SERCA2a) in cardiac muscle cells. Reactivating SERCA2a improves cardiac function in heart failure models, making it a validated targ...
Journal of molecular graphics & modelling
Feb 6, 2025
Power conversion efficiency (PCE) prediction in dye-sensitized solar cells (DSSCs) increasingly relies on computation and machine learning, lowering experimental demands and accelerating materials discovery. In this work we incorporated quantum-chemi...
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Feb 6, 2025
OBJECTIVES: To identify how machine learning (ML) approaches were implemented in mapping studies and to determine the extent to which ML improved performance compared with regression models (RMs).
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Feb 6, 2025
OBJECTIVE: This study introduces a machine learning approach to automate muscle ultrasound analysis, aiming to improve objectivity and efficiency in segmentation, classification, and Heckmatt grading.
The random motion of molecules in living cells has consistently been reported to deviate from standard Brownian motion, a behavior coined as "anomalous diffusion." To study this phenomenon in living cells, fluorescence correlation spectroscopy (FCS) ...
BACKGROUND: Large language models (LLMs) often struggle to fully capture the nuanced preferences and clinical judgement of radiologists in medical report summarization even when fine-tuned on massive medical reports. This could lead to the generated ...
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